{"url":"/task/robot-task-planning","name":"Robot Task Planning","slug":"robot-task-planning","description_markdown":null,"categories":[{"name":"Reasoning","url":"/area/reasoning"},{"name":"Robots","url":"/area/robots"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":48,"papers_with_code":23,"benchmarks":2,"benchmark_tables_in_archive":2,"benchmark_tables_shown":2,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":7,"subtasks":1,"parent_tasks":0},"benchmarks":[{"leaderboard":"/sota/robot-task-planning-on-packit","slug":"robot-task-planning-on-packit","dataset":"PackIt","dataset_url":"/dataset/packit","rows_in_archive":4,"metrics":["Average Reward"],"first_row_in_archive_order":{"model":"PackNN","paper_title":"PackIt: A Virtual Environment for Geometric Planning","paper_url":"/paper/packit-a-virtual-environment-for-geometric","paper_date":"2020-07-21","arxiv_id":"2007.11121","code_links":[{"title":"princeton-vl/PackIt","url":"https://github.com/princeton-vl/PackIt"}],"syntology":{"n":8,"n_ran":0,"n_unverified":8,"n_pointer_only":0}}},{"leaderboard":"/sota/robot-task-planning-on-sheetcopilot","slug":"robot-task-planning-on-sheetcopilot","dataset":"SheetCopilot","dataset_url":"/dataset/sheetcopilot","rows_in_archive":2,"metrics":["Pass@1"],"first_row_in_archive_order":{"model":"SheetAgent (GPT-3.5)","paper_title":"SheetAgent: Towards A Generalist Agent for Spreadsheet Reasoning and Manipulation via Large Language Models","paper_url":"/paper/sheetagent-a-generalist-agent-for-spreadsheet","paper_date":"2024-03-06","arxiv_id":"2403.03636","code_links":[],"syntology":null}}],"datasets":[{"url":"/dataset/packit","name":"PackIt","full_name":"","num_papers_in_archive":3},{"url":"/dataset/sheetcopilot","name":"SheetCopilot","full_name":"","num_papers_in_archive":2},{"url":"/dataset/emmoe-100","name":"EMMOE-100","full_name":"","num_papers_in_archive":1},{"url":"/dataset/hri-simple-tasks","name":"HRI Simple Tasks","full_name":"","num_papers_in_archive":1},{"url":"/dataset/synthetic-object-preference-adaptation-data","name":"Synthetic Object Preference Adaptation Data","full_name":"","num_papers_in_archive":1},{"url":"/dataset/taskography","name":"Taskography","full_name":"PDDLGym Taskography","num_papers_in_archive":1},{"url":"/dataset/fields2benchmark-dataset","name":"Fields2Benchmark dataset","full_name":"","num_papers_in_archive":0}],"subtasks":[{"url":"/task/task-planning","name":"Task Planning"}],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":23,"of":23,"tagged_in_all":48,"items":[{"url":"/paper/do-as-i-can-not-as-i-say-grounding-language","title":"Do As I Can, Not As I Say: Grounding Language in Robotic Affordances","date":"2022-04-04","arxiv_id":"2204.01691","repositories_listed":3,"syntology":null},{"url":"/paper/3d-dynamic-scene-graphs-actionable-spatial","title":"3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans","date":"2020-02-15","arxiv_id":"2002.06289","repositories_listed":3,"syntology":{"n":4,"n_ran":0,"n_unverified":4,"n_pointer_only":0}},{"url":"/paper/training-frankensteins-creature-to-stack","title":"The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints","date":"2018-10-27","arxiv_id":"1810.11714","repositories_listed":3,"syntology":null},{"url":"/paper/you-only-demonstrate-once-category-level","title":"You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration","date":"2022-01-30","arxiv_id":"2201.12716","repositories_listed":2,"syntology":{"n":30,"n_ran":4,"n_unverified":26,"n_pointer_only":0}},{"url":"/paper/llm-map-bimanual-robot-task-planning-using","title":"LLM+MAP: Bimanual Robot Task Planning using Large Language Models and Planning Domain Definition Language","date":"2025-03-21","arxiv_id":"2503.17309","repositories_listed":1,"syntology":null},{"url":"/paper/mrbtp-efficient-multi-robot-behavior-tree","title":"MRBTP: Efficient Multi-Robot Behavior Tree Planning and Collaboration","date":"2025-02-25","arxiv_id":"2502.18072","repositories_listed":1,"syntology":null},{"url":"/paper/robomatrix-a-skill-centric-hierarchical","title":"RoboMatrix: A Skill-centric Hierarchical Framework for Scalable Robot Task Planning and Execution in Open-World","date":"2024-11-29","arxiv_id":"2412.00171","repositories_listed":1,"syntology":null},{"url":"/paper/selp-generating-safe-and-efficient-task-plans","title":"SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Models","date":"2024-09-28","arxiv_id":"2409.19471","repositories_listed":1,"syntology":null},{"url":"/paper/coherent-collaboration-of-heterogeneous-multi","title":"COHERENT: Collaboration of Heterogeneous Multi-Robot System with Large Language Models","date":"2024-09-23","arxiv_id":"2409.15146","repositories_listed":1,"syntology":null},{"url":"/paper/sequential-planning-in-large-partially","title":"Sequential Planning in Large Partially Observable Environments guided by LLMs","date":"2023-12-12","arxiv_id":"2312.07368","repositories_listed":1,"syntology":null},{"url":"/paper/vision-language-interpreter-for-robot-task","title":"Vision-Language Interpreter for Robot Task Planning","date":"2023-11-02","arxiv_id":"2311.00967","repositories_listed":1,"syntology":null},{"url":"/paper/reflect-summarizing-robot-experiences-for","title":"REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction","date":"2023-06-27","arxiv_id":"2306.15724","repositories_listed":1,"syntology":{"n":19,"n_ran":0,"n_unverified":19,"n_pointer_only":0}},{"url":"/paper/robot-task-planning-based-on-large-language","title":"Robot Task Planning Based on Large Language Model Representing Knowledge with Directed Graph Structures","date":"2023-06-08","arxiv_id":"2306.05171","repositories_listed":1,"syntology":null},{"url":"/paper/sheetcopilot-bringing-software-productivity","title":"SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models","date":"2023-05-30","arxiv_id":"2305.19308","repositories_listed":1,"syntology":null},{"url":"/paper/parsel-a-unified-natural-language-framework","title":"Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions","date":"2022-12-20","arxiv_id":"2212.10561","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}},{"url":"/paper/busybot-learning-to-interact-reason-and-plan","title":"BusyBot: Learning to Interact, Reason, and Plan in a BusyBoard Environment","date":"2022-07-17","arxiv_id":"2207.08192","repositories_listed":1,"syntology":null},{"url":"/paper/taskography-evaluating-robot-task-planning","title":"TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphs","date":"2022-07-11","arxiv_id":"2207.05006","repositories_listed":1,"syntology":null},{"url":"/paper/language-models-as-zero-shot-planners-1","title":"Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents","date":"2022-01-18","arxiv_id":"2201.07207","repositories_listed":1,"syntology":null},{"url":"/paper/catgrasp-learning-category-level-task","title":"CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation","date":"2021-09-19","arxiv_id":"2109.09163","repositories_listed":1,"syntology":null},{"url":"/paper/q-attention-enabling-efficient-learning-for","title":"Q-attention: Enabling Efficient Learning for Vision-based Robotic Manipulation","date":"2021-05-31","arxiv_id":"2105.14829","repositories_listed":1,"syntology":null},{"url":"/paper/packit-a-virtual-environment-for-geometric","title":"PackIt: A Virtual Environment for Geometric Planning","date":"2020-07-21","arxiv_id":"2007.11121","repositories_listed":1,"syntology":{"n":8,"n_ran":0,"n_unverified":8,"n_pointer_only":0}},{"url":"/paper/functional-object-oriented-network-1","title":"Task Planning with a Weighted Functional Object-Oriented Network","date":"2019-05-01","arxiv_id":"1905.00502","repositories_listed":1,"syntology":null},{"url":"/paper/visual-robot-task-planning","title":"Visual Robot Task Planning","date":"2018-03-30","arxiv_id":"1804.00062","repositories_listed":1,"syntology":null}],"syntology_records":5,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}